Pradip Nichite
Learn How to Finetune GPT-3 to Get Better Results and Save Cost.
Fine-tuning lets you get more out of the models available through the API by providing:
1. Higher quality results than prompt design.
2. Ability to train on more examples than can fit in a prompt.
3. Token savings due to shorter prompts.
4. Lower latency requests.
Code: https://github.com/PradipNichite/Youtube-Tutorials/blob/main/Youtube_GPT_3_Finetuning.ipynb
GPT-3 Playlist:
https://youtube.com/playlist?list=PLAMHV77MSKJ4QOIS86OiXMtb3-4TUUzho
1. Learn how to build NLP applications using GPT-3. Learn to Write GPT-3 prompt.
2. Learn How to integrate GPT-3 Prompt into Python.
3. Aspect-Based Sentiment Analysis using GPT-3 | Prompt Design
4. GPT-3 Embeddings: Perform Text Similarity, Semantic Search, Classification, and Clustering.
5. Finetuning GPT-3.
I am a Freelance Data Scientist working on Natural Language Processing (NLP) and building end-to-end NLP applications.
I have over 7 years of experience in the industry, including as a Lead Data Scientist at Oracle, where I worked on NLP and MLOps.
I Share Practical hands-on tutorials on NLP and Bite-sized information and knowledge related to Artificial Intelligence.
LinkedIn: https://www.linkedin.com/in/pradipnichite/
#gpt3 #openai #nlp #fintuning #artificalintelligence #machinelearning